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research-article2016
NNRXXX10.1177/1545968315625838Neurorehabilitation and Neural RepairFriel et al
Original Article
Skilled Bimanual Training Drives Motor Cortex Plasticity in Children With Unilateral Cerebral Palsy
Neurorehabilitation and Neural Repair 1–11 © The Author(s) 2016 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/1545968315625838 nnr.sagepub.com
Kathleen M. Friel, PhD1,2,3, Hsing-Ching Kuo, MS2, Jason Fuller, PhD1,4, Claudio L. Ferre, PhD2, Marina Brandão, PhD5, Jason B. Carmel, MD, PhD1,3, Yannick Bleyenheuft, PhD6, Jaimie L. Gowatsky, MA7, Arielle D. Stanford, MD8, Stefan B. Rowny, MD7, Bruce Luber, PhD9, Bruce Bassi, MD7, David L. K. Murphy7, Sarah H. Lisanby, MD10, and Andrew M. Gordon, PhD2,7
Abstract Background. Intensive bimanual therapy can improve hand function in children with unilateral spastic cerebral palsy (USCP). We compared the effects of structured bimanual skill training versus unstructured bimanual practice on motor outcomes and motor map plasticity in children with USCP. Objective. We hypothesized that structured skill training would produce greater motor map plasticity than unstructured practice. Methods. Twenty children with USCP (average age 9.5; 12 males) received therapy in a day camp setting, 6 h/day, 5 days/week, for 3 weeks. In structured skill training (n = 10), children performed progressively more difficult movements and practiced functional goals. In unstructured practice (n = 10), children engaged in bimanual activities but did not practice skillful movements or functional goals. We used the Assisting Hand Assessment (AHA), Jebsen-Taylor Test of Hand Function (JTTHF), and Canadian Occupational Performance Measure (COPM) to measure hand function. We used single-pulse transcranial magnetic stimulation to map the representation of first dorsal interosseous and flexor carpi radialis muscles bilaterally. Results. Both groups showed significant improvements in bimanual hand use (AHA; P < .05) and hand dexterity (JTTHF; P < .001). However, only the structured skill group showed increases in the size of the affected hand motor map and amplitudes of motor evoked potentials (P < .01). Most children who showed the most functional improvements (COPM) had the largest changes in map size. Conclusions. These findings uncover a dichotomy of plasticity: the unstructured practice group improved hand function but did not show changes in motor maps. Skill training is important for driving motor cortex plasticity in children with USCP. Keywords rehabilitation, pediatric, transcranial magnetic stimulation, neuroplasticity, hemiplegia
Introduction
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Unilateral spastic cerebral palsy (USCP) is caused by damage to the developing brain within the first 2 years of life. USCP results in weakness and motor deficits on one side of the body. Improving hand function is a main goal for most children with USCP.1 Intensive bimanual therapy improves hand function in children with USCP.2-6 In our intensive bimanual training model (Hand-Arm Bimanual Intensive Therapy; HABIT), children spend 3 weeks using both upper extremities in play-based activities, 6 h/day.4 Task difficulty systematically increases as motor proficiency progresses, further enhancing improvement.7 We recently showed that HABIT improves unimanual skill, bimanual hand use, and functional hand use.8 Given the functional impact of training, it is important to determine how training affects the brain.
Burke-Cornell Medical Research Institute, White Plains, NY, USA Teachers College, Columbia University, New York, NY, USA 3 Weill Cornell Medical College, New York, NY, USA 4 New York University, New York, NY, USA 5 Universidade Federal de Minas Gerais, Belo Horizonte, Brazil 6 Université Catholique de Louvain, Brussels, Belgium 7 Columbia University Medical Center, New York, NY, USA 8 Alkermes, Inc, Waltham, MA, USA 9 Duke University, Durham, NC, USA 10 Division of Translational Research, National Institutes of Health, Bethesda, MD, USA 2
Supplementary material for this article is available on the Neurorehabilitation & Neural Repair website at http://nnr.sagepub.com/ content/by/supplemental-data. Corresponding Author: Kathleen M. Friel, Burke-Cornell Medical Research Institute, 785 Mamaroneck Avenue, White Plains, NY 10605, USA. Email: [email protected]
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Skill training drives plasticity of the motor system.9-12 Skill training involves progressively greater task difficulty, whereas unskilled use of the hand involves repeating a movement that can be done without learning and does not increase in difficulty.7 Animal models of USCP2 and stroke13-15 have demonstrated the importance of skill training in rehabilitation. Skill training improves motor outcomes and expands the motor map of the affected extremity, while repetitive unskilled use of the affected extremity does not produce map changes or motor recovery.2,11 The brain circuits that underlie motor control in USCP have been well-characterized in an animal model.16 Specifically, work in the USCP model demonstrated that skill training, but not unskilled motor use, drives plasticity of cortical motor maps and corticospinal connections.2 This study leverages our understanding of critical ingredients in USCP rehabilitation in the animal model to test whether skill training changes motor maps and hand function in children with USCP. Several studies have shown that constraint-induced movement therapy produces changes in motor cortex physiology in children with CP17-19 and stroke patients.20-22 Although several studies have examined the effects of constraint and bimanual therapies in children with USCP,6,23-26 to our knowledge, this study is the first to specifically examine the critical ingredients that drive motor cortex plasticity associated with bimanual training in children with USCP. We compared the effects of bimanual therapy that incorporates structured skill training versus unstructured playlike hand use on manual skill in children with USCP. Each group received 90 hours of therapy, 6 hours/day, 3 weeks. During training, children actively used both hands in playbased activities. Structured skill training incorporated 3 key components: (a) progression of task difficulty, (b) repeated practice of isolated movements that are components of a more complex task, and (c) repetition of functional goals, such as tying shoes. Children in the unstructured practice group performed bimanual movements during play, but did not progress skill of activities, nor practice isolated movements or functional goals. In the structured skill training group, task difficulty was increased by imposing greater spatial or temporal constraints, or by providing tasks that required increased skilled use and problem solving.7,8 An example is placing a game board farther away from the child, to encourage a farther reach as a child’s arm extension increased. In the unstructured practice group, no constraints were placed on how a child completed an activity (eg, game board kept in close position). We used single-pulse transcranial magnetic stimulation (TMS) to assess topography and excitability of the motor cortex map of the affected hand before, immediately after, and 6 months after training. We hypothesized that structured skill training, but not unstructured practice, would drive changes in size and excitability of the motor map.
Methods Participants We recruited participants from regional clinics, our website (http://www.tc.edu/centers/cit/), ClinicalTrials.gov (NCT00305006), and online communities. Inclusion criteria were the following: (a) congenital USCP, (b) ability to lift arms 15 cm above table surface and grasp light objects, and (c) cognition similar to their age-specific peers in school. Exclusion criteria were the following: (a) health problems that would interfere with participation, (b) history of seizures after 2 years of age with active use of antiseizure medications, (c) uncorrected visual problems, (d) severe spasticity (Ashworth ≥3), (e) surgery on more-affected hand within 1 year, (f) botulinum toxin in upper extremity within 6 months, and (g) nonremovable metallic objects in body. Informed assent was obtained from participants and consent from caregivers. Procedures were approved by the institutional review boards of Teachers College, Columbia University, where hand training was performed, and the New York State Psychiatric Institute, where brain imaging and motor mapping were acquired.
Interventions Day camps were conducted at Teachers College, Columbia University, during summers 2010 to 2012. Eighteen children were randomized to either structured HABIT (n = 8, structured skill group) or unstructured bimanual play (n = 10, unstructured practice group), performed in separate rooms. Motor outcomes from these children have been published in a larger randomized clinical trial that included 22 children.8 Eighteen of the children in the randomized clinical trial also participated in this TMS mapping study. Two teenagers (ages 15, 17) were assigned to the structured skill group because they were self-motivated to maximize skill demand of activities. This balanced group size at 10 each. Clinical characteristics did not differ between groups (Table 1; χ2 P > .05). Details of materials, methods, randomization, location, and adherence are presented in Supplementary Materials.
Intervention Description Procedures. All interventionists, parents, children, and motor skill assessors were blinded to therapy group and study hypotheses. Children were randomized to receive structured or unstructured HABIT. Participants engaged in age-appropriate bimanual training 6 hours/day for 15 days (90 hours). In both groups, activities were chosen that required use of both hands. If a child stopped using one hand during therapy, interventionists immediately reminded the child to use both hands.
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Friel et al Table 1. Baseline Participant Characteristics. Characteristics
Structured (n = 10)
Mean age in years, months (SD) Gender Male Female Paretic upper extremity Right Left Lesion location Right Left Laterality of motor map by TMS Contralateral Bilateral Ipsilateral Race Asian Caucasian Hispanic Mixed Manual Ability Classification System I II III Baseline AHA, mean (SD), logits Baseline JTTHF, mean (SD), seconds Baseline COPM Performance, mean (SD) Baseline COPM Satisfaction, mean (SD)
Unstructured (n = 10)
9.11 (3.5)
8.11 (2.5)
6 (60%) 4 (40%)
6 (60%) 4 (40%)
6 (60%) 4 (40%)
6 (60%) 4 (40%)
4 6
4 6
1 (10%) 5 (50%) 4 (40%)
3 (30%) 1 (10%) 6 (60%)
0 9 (90%) 1 (10%) 0
1 (10%) 7 (70%) 1 (10%) 1 (10%)
2 (20%) 5 (50%) 3 (30%) 58.5 (8.3) 286.7 (239) 3.6 (1.8) 3.2 (2.2)
2 (20%) 6 (60%) 2 (20%) 63.3 (11.5) 225.2 (166) 3.1 (0.9) 3.6 (1.5)
Abbreviations: SD, standard deviation; AHA, Assisting Hand Assessment; JTTHF, Jebsen-Taylor Test of Hand Function; COPM, Canadian Occupational Performance Measure.
Table 2. Similarities and Differences Between Treatment Groups. Treatment Characteristic
Structured
Unstructured
Treatment duration Ratio interventionist to child Homework (1 hour/day) during training and for 6 months after training Focus on bimanual practice Skill progression during therapy Practiced shaping of movements Practiced functional goals
90 hours At least 1:1 Yes Yes Yes Yes Yes
90 hours At least 1:1 Yes Yes No No No
Structured HABIT. This group consisted of 10 children. Structured HABIT4,5,27 differed from unstructured bimanual training in 3 ways (Table 2): (a) progression of task difficulty, (b) repeated practice of isolated movements, and (c) practice of functional goals. Progression of task difficulty. Task difficulty was graded by either increasing the temporal and spatial complexity of the movements or by increasing the complexity of how the affected hand was used.
Repeated practice of isolated movements. Part-task practice (shaping) emphasized practice of a single movement component. Task performance, time on task, and number of repetitions were logged. Practice of functional goals. Play goals, such as dribbling a basketball, and activity of daily living goals, such as tying shoes, were determined by the participant and their family before training. Goals were practiced during training.
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Unstructured Bimanual Training. Children (n = 10) were engaged in intensive use of both hands, without focus on skill. Bimanual activities were selected according to the child’s interest. Interventionists were trained only to provide activities that required use of both hands in a playful context. They were told that the emphasis was on having fun rather than rehabilitation. The supervisor ensured interventionists provided no increase in task complexity, no guidance on how to use the affected hand, and no gradation of task demands. The participants did not practice functional goals or part-task practice of movement components.
Behavioral Measures Participants were evaluated prior to treatment, within 2 days after treatment, and 6 months later by a physical therapist blinded to group allocation. Three outcome measures were used to quantify unimanual capacity, bimanual performance, and functional goals, based on the International Classification of Functioning, Disability, and Health. We quantified unilateral dexterity using the JebsenTaylor Test of Hand Function (JTTHF).28 Participants use one hand to perform functional movements, including flipping cards, manipulating/placing small objects, simulated eating, checker stacking, and manipulating cans. The outcome is the time (seconds) to perform movements. To quantify how the hands function together, we employed the Assisting Hand Assessment (AHA).29,30 The AHA quantifies the effectiveness of assisting hand use in performing bimanual activities in children with unilateral upper limb disabilities. The AHA has excellent validity, reliability (0.97-0.99), and responsiveness to change.8,29 The test was videotaped and scored off-site by an experienced blinded evaluator. Scores were computed as transformed logits (AHA units). To measure performance and satisfaction levels in functional goals, we employed the Canadian Occupational Performance Measure (COPM).31 The COPM is a standardized measure that identifies goals and detects changes in self-care, productivity, and leisure performance areas. Through interview, the caregiver identified the child’s functional goals and ranked their importance. They rated satisfaction and performance of each goal (maximum 5). Mean performance and satisfaction scores were analyzed. Both groups of children set goals, but only the structured group practiced goals during the intervention.
(FCR) muscles bilaterally. TMS details are presented in Supplementary Materials. Each child’s TMS map was colocalized to their structural magnetic resonance imaging (MRI), to allow motor mapping that was consistent between each time point. Details are presented in Supplementary Materials. TMS-evoked motor responses were recorded with surface EMG electrodes. Electrodes were connected to a Brainvision ExG amplifier (NeuroConn, Ilmenau, Germany). TMS pulses were first delivered to the affected hemisphere to search for an EMG response (motor evoked potential [MEP]) of the affected FDI. If an MEP of the affected FDI could not be elicited in the affected hemisphere, the uninjured hemisphere was probed for MEPs of the affected FDI. In all cases, if an MEP of the affected FDI or FCR was not found in the injured hemisphere, it was found in the uninjured hemisphere. We determined the threshold for provoking an MEP. The TMS coil was held at the location that provoked the largest FDI response (“hotspot”). MEPs were evoked beginning at a suprathreshold stimulus intensity. Stimulator output was lowered at 2% increments. The lowest stimulator output at which MEP responses of the affected FDI could be elicited from 5 of 10 pulses was defined as the motor threshold (MT). An MEP was categorized as a response if the latency between the TMS pulse and MEP onset was less than 40 ms, and if the amplitude of the MEP was at least 50 µV. After the MT was determined, a circular grid was superimposed onto the child’s MRI using Brainsight. The grid was centered at the affected FDI hotspot. Grid spacing was 1 cm. The grid consisted of 5 concentric rings, resulting in a grid with a 5 cm radius (81 grid points). Single TMS pulses (3-6 per site when an MEP was found, 1-2 per site when no MEP was found) were delivered to each grid point, starting at the hotspot and moving concentrically along the grid, ending at the outermost ring. Stimuli were delivered at an intensity of 110% affected FDI MT, frequency .3). Six children (5 structured, 1 unstructured) had motor maps of the affected hand in both hemispheres—that is, bilateral motor maps. There was a strong asymmetry in map size of the 2 sides. In 5 of the 6 cases (4 structured, 1 unstructured), the map in the injured hemisphere was approximately double the size of the map in the other hemisphere (ratio, injured–uninjured hemispheres = 1.95, SD = 0.11). For these cases, we used the map in the injured hemisphere for analysis. In the remaining child with bilateral maps (structured group), the map of the affected FDI and FCR was 4.75× larger in the uninjured hemisphere than the injured hemisphere, and the map in the uninjured hemisphere was used for analyses.
Changes in Motor Maps After Bimanual Training
Figure 2. Coronal MRI slices showing a cross-section of each child’s lesion.
The color of the frame surrounding the MRI indicates the CST laterality of the child (black = contralateral, white = bilateral, gray = ipsilateral). The yellow asterisk indicates the side of injury.
hand. There was also an overall improvement in COPMSatisfaction (Figure 1D; F[2, 17] = 15.77, P < .001) but no interaction between COPM-Satisfaction and training type (F[2, 17] = 1.76, P = .20). Both groups improved a clinically meaningful amount in COPM-Performance and Satisfaction. Improvements in all measures were maintained 6 months after therapy, as there were no statistically significant changes between the immediate posttraining and 6 months posttraining measures for either group.
Laterality of Motor Map Controlling the Impaired Hand We determined the location of the motor map of the affected hand (Table 1, Figure 2). Children were categorized as contralateral if 100% of TMS responses in the affected hand resided in the same hemisphere as the lesion. Children were categorized as ipsilateral if 100% of TMS responses in the affected hand resided in the opposite hemisphere as the
We examined changes in motor maps after structured skill training or unstructured practice. Figure 3 shows representative motor maps from one child per group. Map size increased in the structured (1A-1C), but not the unstructured group (2A-C). After training, there was a significant interaction between map size (FDI + FCR) of the affected hand and training type (F[2, 17] = 4.7, P = .036). There was a significant increase in map size of the affected hand in the structured skill group (pre-post training P = .009, 23.3% increase; pretraining to 6 months posttraining P = .047, 34.9% increase) but not in the unstructured practice group (P > .3; .2). The map size for the affected FCR did not change significantly in the structured skill group immediately after training (P = .85, 6.1% increase) but was significantly greater than baseline 6 months after training (P = .049, 42.2% increase). In the unstructured group, FCR map size did not change after training (P > .3). Amplitude of motor responses to TMS increased significantly (Figure 4) after structured skill training but not unstructured practice (Figure 4D-E). There was a significant interaction between average MEP of the affected FDI and treatment group (F[2, 17] = 4.21, P = .033). The structured skill group showed a significant increase in FDI MEP size from pretraining to 6 months posttraining (P < .0001, 19% increase), though not from pretraining to immediately following or immediately following to 6 months later. There was no significant change in FDI MEP size in the unstructured practice group (P > .8). There was a significant
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Figure 3. Changes in motor maps after training.
Colored dots represent movement evoked by TMS at that site. (A1-C1) Structured skill training, representative maps of the affected hand from one child. (A2-C2) Unstructured practice, representative maps of the affected hand from one child. (D) Quantification of map changes. The size of the motor map of the affected hand increased significantly only in the structured training group (*P < .05).
interaction between average MEP of the affected FCR and group (F[2, 17] = 4.96, P = .019). The structured skill group showed a significant increase in FCR MEP size from pretraining to 6 months posttraining (P < .0001, 78.1% increase) but not pretraining to immediate posttraining. There was no significant change in FCR MEP size in the unstructured practice group (P > .9).
Plasticity of Ipsilateral Versus Contralateral Maps We determined the location of the motor map of the affected hand (Table 1). There was no difference in the distribution of hand map laterality (contralateral or ipsilateral to affected hand) between groups (Fisher’s, P = .85). Representative maps are shown in Figure 2 (contralateral) and Figure 3 (ipsilateral). Both ipsilateral and contralateral maps expanded after structured skill HABIT (F[2, 8] = 4.6, P = .048). The magnitude of map changes were not different in children with an ipsilateral versus contralateral CST (F[2, 7] = 0.32, P = .74).
Associations Between Map Changes and Hand Function Changes Children in the structured skill group who showed the most improvement in COPM-Performance also had the largest changes in hand map size (Supplemental Figure 1, F[1, 8] = 7.5,
P = .013, r = .54, r2 = .30). Children with larger improvements in JTTHF showed larger expansions of the hand motor map (F[1, 8] = 5.6, P = .045, r = .64, r2 = .41). There was not a significant association between hand map change and improvement in the AHA (P = .95, r = .02). In the unstructured group, there were no significant associations between map changes and JTTHF, AHA, or COPM changes (P > .3, r < .35). Importantly, baseline hand function and amount of recovery was not related to whether the child’s map of the impaired hand was located in the injured or uninjured hemisphere (JTTHF F[1, 18] = 4.82, P = .10; AHA, F[1, 18] = 1.4, P = .24; COPM Performance, F[1, 18] = 0.42, P = .48, no interactions).
Stability of Motor Maps in the Absence of Intervention We show the stability of motor maps in the absence of intervention (Supplementary Materials).
TMS Safety Outcomes Of the 70 TMS sessions conducted in this study, 2 participants reported mild headache after 4 (5.7%) of the sessions, 3 participants reported discomfort in the headband used for neuronavigation after 5 (7.1%) of the sessions, and 2 participants reported discomfort with sitting for an extended
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Figure 4. Changes in magnitude of motor evoked potentials in TMS maps after structured skill training.
(A1-C1) Maps of the affected hand located contralateral to the affected hemisphere in a representative case. Red color indicates stronger MEP response. (A2-C2) Representative maps of the affected hand in a representative case from the unstructured practice group. (D-E) MEP amplitude of the representation of the affected FDI increased significantly after structured but not unstructured training (*P < .05).
period of time after 3 (4.3%) sessions. All side effects resolved without treatment within 1 hour after TMS. No serious adverse events occurred.
Discussion This is the first study, to our knowledge, to examine the critical ingredients of bimanual training that drive changes in motor cortex physiology in children with USCP. We compared bimanual structured skill training and unstructured practice. The study uncovered 3 main findings: (a) skill training increased the size and strength of the motor map of the affected hand, (b) unimanual skill of the affected hand and performance of functional goals were correlated with increased map size, and (c) Motor maps were plastic whether they resided in the hemisphere contralateral or ipsilateral to the affected hand. Our findings are consistent with studies showing that repetitive practice of a specific motor skill drives map plasticity.2,11,12,33-35 In animal models of stroke and USCP, and in human stroke patients, constraint of the unaffected forelimb, plus skill training of the affected forelimb, can improve motor skill and expand the motor map of the affected limb.21,22,36-40 In human stroke patients, the magnitude of map expansion was correlated with improvements in skill.41 Training has also been shown to increase fMRI activations in secondary motor and cerebellar regions.42
Importantly, constraint alone, without skill training, does not change motor maps.2,11 Though further work is needed to uncover the mechanisms of cortical plasticity associated with skill-based neurorehabilitation, work in animal models has determined that skill training, but not unskilled motor activity, increases densities of synapses, dendritic arbors, and spines in the motor networks.43 These changes are associated with increases in neurotrophin expression44 and increased density of spinal interneurons.2 We found that structured and unstructured therapy both resulted in equal improvements in unimanual movement speed and bimanual use. It is possible that the 2 groups had differences in movement kinematics or other more detailed measures of movement quality, since the clinical outcome measures we used do not quantify the quality of movements. Further studies should examine kinematics of motor recovery in children with USCP. We found that functional gains and changes in cortical plasticity were independent of hemisphere of control, that is, ipsilateral or contralateral to the affected hand. Constraint-induced movement therapy studies in children with USCP suggested that in children with ipsilateral control of the affected hand, improvements in movement speed45 and changes in M1 excitability17 were less robust than for children with a contralateral CST. However, we found that ipsilateral control of the affected limb showed
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Friel et al similar amounts of plasticity as contralateral control. Ipsilateral pathways have the capacity to be adaptive, functional, and plastic,46-48 though a larger study is needed to better understand differences in plasticity of different hemispheres of control. This study uncovers a dichotomy of neuroplasticity. The unstructured practice group, which improved hand function, did not show motor cortex plasticity in TMS maps. The high dose (90 hours) may have washed out group differences. Lower dosages could result in differences between groups. While we did find a positive association between functional gains and cortical plasticity, it is possible that with lower doses, associations between motor outcomes and plasticity would be more apparent in the structured skill group than the unstructured group. Changes in motor function can occur without causing changes in motor maps.2,9 Some improvements in motor skill can be driven by existing motor networks, while more robust changes in motor skill are associated with rewiring of motor pathways.49 It is also likely that plasticity occurred in brain regions other than M1, such as secondary motor areas, sensory networks,50-52 subcortical brain structures,53 and spinal interneuronal systems.2,35,54 It is likely that plasticity in these systems underlies the motor improvements seen in the unstructured practice group. Further studies, specifically those that can measure plasticity in different brain regions, are needed to examine plasticity in other systems during rehabilitation. The relative timing of motor map changes and improvements in motor skill has been studied in animal models of stroke and USCP. Behavioral improvements after infarct plateaued before changes in motor maps could be detected.55,56 In contrast, in USCP, map changes were found after pharmacotherapy57 or constraint-induced movement therapy2 that preceded motor recovery. It is possible that intensity of the structured skill group was sufficient to drive motor map plasticity, but that a longer duration of unstructured practice may have been needed to change motor maps. The current findings show that skill training is a critical ingredient for driving motor cortical plasticity in children with USCP. While both groups improved in clinical outcomes, the structured skill training group showed the most improvement in functional gains. This work and other evidence58 indicate that skill training is an important ingredient in neurorehabilitation strategies.
Methods that examine cortical plasticity throughout the brain, such as functional MRI and electroencephalography, can determine other locations of plasticity associated with hand rehabilitation. We discuss challenges of applying our methods to children with USCP in Supplemental Materials. Finally, clinical outcomes reported here measure indirect aspect of movement quality. Further study of movement quality is needed to explore the relationship between cortical plasticity and rehabilitation outcomes.
Conclusions Structured and unstructured bimanual training improved hand function in children with USCP. Skill training produced stronger improvements in functional goals. There was a dichotomy between these improvements and cortical plasticity. Only skilled training induced motor map plasticity. Further work is needed to examine the interplay between cortical physiology and motor skill improvements. Acknowledgments We thank Ya-Ching Hng, Electra Petra, Ashley Chinnan, and the volunteer interventionists. We thank Stephen Dashnaw and Glenn Castillo for MRI acquisition. We thank Drs Peter Bulow and Joshua Berman for performing screening exams. We thank the participants and their families.
Authors’ Note None of the sponsors were involved in the preparation of the manuscript or decision to submit for publication.
Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Funded by NS062116 (KMF), Columbia Professional Schools Diversity Award (KMF), and NIH CTSA Award (KMF) (KL2 RR024157, UL1 RR024156, TL1 RR024158). Each of these sponsors provided funding based on the design of the study. Funds were used to pay for equipment and personnel needed for data collection, management, analysis, and interpretation.
References
Limitations This study has several limitations. The relatively low number of participants limits generalizability. While we did match groups on baseline JTTHF and age, there were differences between groups in the distribution of CST projection patterns. Second, this study only measured M1 plasticity.
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18. Cao J, Khan B, Hervey N, et al. Evaluation of cortical plasticity in children with cerebral palsy undergoing constraintinduced movement therapy based on functional near-infrared spectroscopy. J Biomed Opt. 2015;20(4):046009. 19. Inguaggiato E, Sgandurra G, Perazza S, Guzzetta A, Cioni G. Brain reorganization following intervention in children with congenital hemiplegia: a systematic review. Neural Plast. 2013;2013:356275. 20. Kononen M, Tarkka IM, Niskanen E, et al. Functional MRI and motor behavioral changes obtained with constraintinduced movement therapy in chronic stroke. Eur J Neurol. 2012;19:578-586. 21. Liepert J, Miltner WH, Bauder H, et al. Motor cortex plasticity during constraint-induced movement therapy in stroke patients. Neurosci Lett. 1998;250:5-8. 22. Park SW, Butler AJ, Cavalheiro V, Alberts JL, Wolf SL. Changes in serial optical topography and TMS during task performance after constraint-induced movement therapy in stroke: a case study. Neurorehabil Neural Repair. 2004;18: 95-105. 23. Hoare BJ, Wasiak J, Imms C, Carey L. Constraint-induced movement therapy in the treatment of the upper limb in children with hemiplegic cerebral palsy. Cochrane Database Syst Rev. 2007;(2):CD004149. 24. Boyd R, Sakzewski L, Ziviani J, et al. INCITE: a randomised trial comparing constraint induced movement therapy and bimanual training in children with congenital hemiplegia. BMC Neurol. 2010;10:4. 25. Aarts PB, Jongerius PH, Geerdink YA, van Limbeek J, Geurts AC. Effectiveness of modified constraint-induced movement therapy in children with unilateral spastic cerebral palsy: a randomized controlled trial. Neurorehabil Neural Repair. 2010;24:509-518. 26. Facchin P, Rosa-Rizzotto M, Visona Dalla Pozza L, et al. Multisite trial comparing the efficacy of constraint-induced movement therapy with that of bimanual intensive training in children with hemiplegic cerebral palsy: postintervention results. Am J Phys Med Rehabil. 2011;90:539-553. 27. Charles JR, Wolf SL, Schneider JA, Gordon AM. Efficacy of a child-friendly form of constraint-induced movement therapy in hemiplegic cerebral palsy: a randomized control trial. Dev Med Child Neurol. 2006;48:635-642. 28. Jebsen RH, Taylor N, Trieschmann RB, Trotter MJ, Howard LA. An objective and standardized test of hand function. Arch Phys Med Rehabil. 1969;50:311-319. 29. Holmefur M, Krumlinde-Sundholm L, Eliasson AC. Interrater and intrarater reliability of the Assisting Hand Assessment. Am J Occup Ther. 2007;61:79-84. 30. Krumlinde-Sundholm L, Holmefur M, Kottorp A, Eliasson AC. The Assisting Hand Assessment: current evidence of validity, reliability, and responsiveness to change. Dev Med Child Neurol. 2007;49:259-264. 31. Law M, Baptiste S, McColl M, Opzoomer A, Polatajko H, Pollock N. The Canadian Occupational Performance Measure: an outcome measure for occupational therapy. Can J Occup Ther. 1990;57:82-87. 32. Sawaki L, Butler AJ, Leng X, et al. Differential patterns of cortical reorganization following constraint-induced
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Friel et al movement therapy during early and late period after stroke: a preliminary study. NeuroRehabilitation. 2014;35:415-426. 33. Kleim JA, Barbay S, Cooper NR, et al. Motor learning-dependent synaptogenesis is localized to functionally reorganized motor cortex. Neurobiol Learn Mem. 2002;77:63-77. 34. Nudo RJ, Milliken GW, Jenkins WM, Merzenich MM. Usedependent alterations of movement representations in primary motor cortex of adult squirrel monkeys. J Neurosci. 1996;16:785-807. 35. Chakrabarty S, Shulman B, Martin JH. Activity-dependent codevelopment of the corticospinal system and target interneurons in the cervical spinal cord. J Neurosci. 2009;29: 8816-8827. 36. Wolf SL, Blanton S, Baer H, Breshears J, Butler AJ. Repetitive task practice: a critical review of constraint-induced movement therapy in stroke. Neurologist. 2002;8:325-338. 37. Liepert J, Graef S, Uhde I, Leidner O, Weiller C. Traininginduced changes of motor cortex representations in stroke patients. Acta Neurol Scand. 2000;101:321-326. 38. Classen J, Liepert J, Wise SP, Hallett M, Cohen LG. Rapid plasticity of human cortical movement representation induced by practice. J Neurophysiol. 1998;79:1117-1123. 39. Liepert J, Bauder H, Wolfgang HR, Miltner WH, Taub E, Weiller C. Treatment-induced cortical reorganization after stroke in humans. Stroke. 2000;31:1210-1216. 40. Liepert J. Motor cortex excitability in stroke before and after constraint-induced movement therapy. Cogn Behav Neurol. 2006;19:41-47. 41. Sawaki L, Butler AJ, Leng X, et al. Constraint-induced movement therapy results in increased motor map area in subjects 3 to 9 months after stroke. Neurorehabil Neural Repair. 2008;22:505-513. 42. Johansen-Berg H, Dawes H, Guy C, Smith SM, Wade DT, Matthews PM. Correlation between motor improvements and altered fMRI activity after rehabilitative therapy. Brain. 2002;125:2731-2742. 43. Warraich Z, Kleim JA. Neural plasticity: the biological substrate for neurorehabilitation. PM R. 2010;2(12 suppl 2):S208-S219. 44. Boyce VS, Mendell LM. Neurotrophins and spinal circuit function. Front Neural Circuits. 2014;8:59. 45. Kuhnke N, Juenger H, Walther M, Berweck S, Mall V, Staudt M. Do patients with congenital hemiparesis and ipsilateral corticospinal projections respond differently to constraint-induced movement therapy? Dev Med Child Neurol. 2008;50:898-903.
46. Mackey A, Stinear C, Stott S, Byblow WD. Upper limb function and cortical organization in youth with unilateral cerebral palsy. Front Neurol. 2014;5:117. 47. Carmel JB, Kimura H, Martin JH. Electrical stimulation of motor cortex in the uninjured hemisphere after chronic unilateral injury promotes recovery of skilled locomotion through ipsilateral control. J Neurosci. 2014;34:462-466. 48. Reitmeir R, Kilic E, Kilic U, et al. Post-acute delivery of erythropoietin induces stroke recovery by promoting perilesional tissue remodelling and contralesional pyramidal tract plasticity. Brain. 2011;134(pt 1):84-99. 49. Marshall RS, Zarahn E, Alon L, Minzer B, Lazar RM, Krakauer JW. Early imaging correlates of subsequent motor recovery after stroke. Ann Neurol. 2009;65:596-602. 50. Loubinoux I, Carel C, Alary F, et al. Within-session and between-session reproducibility of cerebral sensorimotor activation: a test–retest effect evidenced with functional magnetic resonance imaging. J Cereb Blood Flow Metab. 2001;21: 592-607. 51. Loubinoux I, Carel C, Pariente J, et al. Correlation between cerebral reorganization and motor recovery after subcortical infarcts. Neuroimage. 2003;20:2166-2180. 52. Loubinoux I, Dechaumont-Palacin S, Castel-Lacanal E, et al. Prognostic value of FMRI in recovery of hand function in subcortical stroke patients. Cereb Cortex. 2007;17: 2980-2987. 53. Carey LM, Abbott DF, Egan GF, et al. Evolution of brain activation with good and poor motor recovery after stroke. Neurorehabil Neural Repair. 2006;20:24-41. 54. Chakrabarty S, Martin JH. Postnatal development of a segmental switch enables corticospinal tract transmission to spinal forelimb motor circuits. J Neurosci. 2010;30: 2277-2288. 55. Nishibe M, Urban ET, Barbay S, Nudo RJ. Rehabilitative training promotes rapid motor recovery but delayed motor map reorganization in a rat cortical ischemic infarct model. Neurorehabil Neural Repair. 2014;29:472-482. 56. Eisner-Janowicz I, Barbay S, Hoover E, et al. Early and late changes in the distal forelimb representation of the supplementary motor area after injury to frontal motor areas in the squirrel monkey. J Neurophysiol. 2008;100:1498-1512. 57. Chakrabarty S, Friel KM, Martin JH. Activity-dependent plasticity improves M1 motor representation and corticospinal tract connectivity. J Neurophysiol. 2009;101:1283-1293. 58. Kitago T, Krakauer JW. Motor learning principles for neurorehabilitation. Handb Clin Neurol. 2013;110:93-103.
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research-article2016
NNRXXX10.1177/1545968315625838Neurorehabilitation and Neural RepairFriel et al
Original Article
Skilled Bimanual Training Drives Motor Cortex Plasticity in Children With Unilateral Cerebral Palsy
Neurorehabilitation and Neural Repair 1–11 © The Author(s) 2016 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/1545968315625838 nnr.sagepub.com
Kathleen M. Friel, PhD1,2,3, Hsing-Ching Kuo, MS2, Jason Fuller, PhD1,4, Claudio L. Ferre, PhD2, Marina Brandão, PhD5, Jason B. Carmel, MD, PhD1,3, Yannick Bleyenheuft, PhD6, Jaimie L. Gowatsky, MA7, Arielle D. Stanford, MD8, Stefan B. Rowny, MD7, Bruce Luber, PhD9, Bruce Bassi, MD7, David L. K. Murphy7, Sarah H. Lisanby, MD10, and Andrew M. Gordon, PhD2,7
Abstract Background. Intensive bimanual therapy can improve hand function in children with unilateral spastic cerebral palsy (USCP). We compared the effects of structured bimanual skill training versus unstructured bimanual practice on motor outcomes and motor map plasticity in children with USCP. Objective. We hypothesized that structured skill training would produce greater motor map plasticity than unstructured practice. Methods. Twenty children with USCP (average age 9.5; 12 males) received therapy in a day camp setting, 6 h/day, 5 days/week, for 3 weeks. In structured skill training (n = 10), children performed progressively more difficult movements and practiced functional goals. In unstructured practice (n = 10), children engaged in bimanual activities but did not practice skillful movements or functional goals. We used the Assisting Hand Assessment (AHA), Jebsen-Taylor Test of Hand Function (JTTHF), and Canadian Occupational Performance Measure (COPM) to measure hand function. We used single-pulse transcranial magnetic stimulation to map the representation of first dorsal interosseous and flexor carpi radialis muscles bilaterally. Results. Both groups showed significant improvements in bimanual hand use (AHA; P < .05) and hand dexterity (JTTHF; P < .001). However, only the structured skill group showed increases in the size of the affected hand motor map and amplitudes of motor evoked potentials (P < .01). Most children who showed the most functional improvements (COPM) had the largest changes in map size. Conclusions. These findings uncover a dichotomy of plasticity: the unstructured practice group improved hand function but did not show changes in motor maps. Skill training is important for driving motor cortex plasticity in children with USCP. Keywords rehabilitation, pediatric, transcranial magnetic stimulation, neuroplasticity, hemiplegia
Introduction
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Unilateral spastic cerebral palsy (USCP) is caused by damage to the developing brain within the first 2 years of life. USCP results in weakness and motor deficits on one side of the body. Improving hand function is a main goal for most children with USCP.1 Intensive bimanual therapy improves hand function in children with USCP.2-6 In our intensive bimanual training model (Hand-Arm Bimanual Intensive Therapy; HABIT), children spend 3 weeks using both upper extremities in play-based activities, 6 h/day.4 Task difficulty systematically increases as motor proficiency progresses, further enhancing improvement.7 We recently showed that HABIT improves unimanual skill, bimanual hand use, and functional hand use.8 Given the functional impact of training, it is important to determine how training affects the brain.
Burke-Cornell Medical Research Institute, White Plains, NY, USA Teachers College, Columbia University, New York, NY, USA 3 Weill Cornell Medical College, New York, NY, USA 4 New York University, New York, NY, USA 5 Universidade Federal de Minas Gerais, Belo Horizonte, Brazil 6 Université Catholique de Louvain, Brussels, Belgium 7 Columbia University Medical Center, New York, NY, USA 8 Alkermes, Inc, Waltham, MA, USA 9 Duke University, Durham, NC, USA 10 Division of Translational Research, National Institutes of Health, Bethesda, MD, USA 2
Supplementary material for this article is available on the Neurorehabilitation & Neural Repair website at http://nnr.sagepub.com/ content/by/supplemental-data. Corresponding Author: Kathleen M. Friel, Burke-Cornell Medical Research Institute, 785 Mamaroneck Avenue, White Plains, NY 10605, USA. Email: [email protected]
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Skill training drives plasticity of the motor system.9-12 Skill training involves progressively greater task difficulty, whereas unskilled use of the hand involves repeating a movement that can be done without learning and does not increase in difficulty.7 Animal models of USCP2 and stroke13-15 have demonstrated the importance of skill training in rehabilitation. Skill training improves motor outcomes and expands the motor map of the affected extremity, while repetitive unskilled use of the affected extremity does not produce map changes or motor recovery.2,11 The brain circuits that underlie motor control in USCP have been well-characterized in an animal model.16 Specifically, work in the USCP model demonstrated that skill training, but not unskilled motor use, drives plasticity of cortical motor maps and corticospinal connections.2 This study leverages our understanding of critical ingredients in USCP rehabilitation in the animal model to test whether skill training changes motor maps and hand function in children with USCP. Several studies have shown that constraint-induced movement therapy produces changes in motor cortex physiology in children with CP17-19 and stroke patients.20-22 Although several studies have examined the effects of constraint and bimanual therapies in children with USCP,6,23-26 to our knowledge, this study is the first to specifically examine the critical ingredients that drive motor cortex plasticity associated with bimanual training in children with USCP. We compared the effects of bimanual therapy that incorporates structured skill training versus unstructured playlike hand use on manual skill in children with USCP. Each group received 90 hours of therapy, 6 hours/day, 3 weeks. During training, children actively used both hands in playbased activities. Structured skill training incorporated 3 key components: (a) progression of task difficulty, (b) repeated practice of isolated movements that are components of a more complex task, and (c) repetition of functional goals, such as tying shoes. Children in the unstructured practice group performed bimanual movements during play, but did not progress skill of activities, nor practice isolated movements or functional goals. In the structured skill training group, task difficulty was increased by imposing greater spatial or temporal constraints, or by providing tasks that required increased skilled use and problem solving.7,8 An example is placing a game board farther away from the child, to encourage a farther reach as a child’s arm extension increased. In the unstructured practice group, no constraints were placed on how a child completed an activity (eg, game board kept in close position). We used single-pulse transcranial magnetic stimulation (TMS) to assess topography and excitability of the motor cortex map of the affected hand before, immediately after, and 6 months after training. We hypothesized that structured skill training, but not unstructured practice, would drive changes in size and excitability of the motor map.
Methods Participants We recruited participants from regional clinics, our website (http://www.tc.edu/centers/cit/), ClinicalTrials.gov (NCT00305006), and online communities. Inclusion criteria were the following: (a) congenital USCP, (b) ability to lift arms 15 cm above table surface and grasp light objects, and (c) cognition similar to their age-specific peers in school. Exclusion criteria were the following: (a) health problems that would interfere with participation, (b) history of seizures after 2 years of age with active use of antiseizure medications, (c) uncorrected visual problems, (d) severe spasticity (Ashworth ≥3), (e) surgery on more-affected hand within 1 year, (f) botulinum toxin in upper extremity within 6 months, and (g) nonremovable metallic objects in body. Informed assent was obtained from participants and consent from caregivers. Procedures were approved by the institutional review boards of Teachers College, Columbia University, where hand training was performed, and the New York State Psychiatric Institute, where brain imaging and motor mapping were acquired.
Interventions Day camps were conducted at Teachers College, Columbia University, during summers 2010 to 2012. Eighteen children were randomized to either structured HABIT (n = 8, structured skill group) or unstructured bimanual play (n = 10, unstructured practice group), performed in separate rooms. Motor outcomes from these children have been published in a larger randomized clinical trial that included 22 children.8 Eighteen of the children in the randomized clinical trial also participated in this TMS mapping study. Two teenagers (ages 15, 17) were assigned to the structured skill group because they were self-motivated to maximize skill demand of activities. This balanced group size at 10 each. Clinical characteristics did not differ between groups (Table 1; χ2 P > .05). Details of materials, methods, randomization, location, and adherence are presented in Supplementary Materials.
Intervention Description Procedures. All interventionists, parents, children, and motor skill assessors were blinded to therapy group and study hypotheses. Children were randomized to receive structured or unstructured HABIT. Participants engaged in age-appropriate bimanual training 6 hours/day for 15 days (90 hours). In both groups, activities were chosen that required use of both hands. If a child stopped using one hand during therapy, interventionists immediately reminded the child to use both hands.
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Friel et al Table 1. Baseline Participant Characteristics. Characteristics
Structured (n = 10)
Mean age in years, months (SD) Gender Male Female Paretic upper extremity Right Left Lesion location Right Left Laterality of motor map by TMS Contralateral Bilateral Ipsilateral Race Asian Caucasian Hispanic Mixed Manual Ability Classification System I II III Baseline AHA, mean (SD), logits Baseline JTTHF, mean (SD), seconds Baseline COPM Performance, mean (SD) Baseline COPM Satisfaction, mean (SD)
Unstructured (n = 10)
9.11 (3.5)
8.11 (2.5)
6 (60%) 4 (40%)
6 (60%) 4 (40%)
6 (60%) 4 (40%)
6 (60%) 4 (40%)
4 6
4 6
1 (10%) 5 (50%) 4 (40%)
3 (30%) 1 (10%) 6 (60%)
0 9 (90%) 1 (10%) 0
1 (10%) 7 (70%) 1 (10%) 1 (10%)
2 (20%) 5 (50%) 3 (30%) 58.5 (8.3) 286.7 (239) 3.6 (1.8) 3.2 (2.2)
2 (20%) 6 (60%) 2 (20%) 63.3 (11.5) 225.2 (166) 3.1 (0.9) 3.6 (1.5)
Abbreviations: SD, standard deviation; AHA, Assisting Hand Assessment; JTTHF, Jebsen-Taylor Test of Hand Function; COPM, Canadian Occupational Performance Measure.
Table 2. Similarities and Differences Between Treatment Groups. Treatment Characteristic
Structured
Unstructured
Treatment duration Ratio interventionist to child Homework (1 hour/day) during training and for 6 months after training Focus on bimanual practice Skill progression during therapy Practiced shaping of movements Practiced functional goals
90 hours At least 1:1 Yes Yes Yes Yes Yes
90 hours At least 1:1 Yes Yes No No No
Structured HABIT. This group consisted of 10 children. Structured HABIT4,5,27 differed from unstructured bimanual training in 3 ways (Table 2): (a) progression of task difficulty, (b) repeated practice of isolated movements, and (c) practice of functional goals. Progression of task difficulty. Task difficulty was graded by either increasing the temporal and spatial complexity of the movements or by increasing the complexity of how the affected hand was used.
Repeated practice of isolated movements. Part-task practice (shaping) emphasized practice of a single movement component. Task performance, time on task, and number of repetitions were logged. Practice of functional goals. Play goals, such as dribbling a basketball, and activity of daily living goals, such as tying shoes, were determined by the participant and their family before training. Goals were practiced during training.
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Unstructured Bimanual Training. Children (n = 10) were engaged in intensive use of both hands, without focus on skill. Bimanual activities were selected according to the child’s interest. Interventionists were trained only to provide activities that required use of both hands in a playful context. They were told that the emphasis was on having fun rather than rehabilitation. The supervisor ensured interventionists provided no increase in task complexity, no guidance on how to use the affected hand, and no gradation of task demands. The participants did not practice functional goals or part-task practice of movement components.
Behavioral Measures Participants were evaluated prior to treatment, within 2 days after treatment, and 6 months later by a physical therapist blinded to group allocation. Three outcome measures were used to quantify unimanual capacity, bimanual performance, and functional goals, based on the International Classification of Functioning, Disability, and Health. We quantified unilateral dexterity using the JebsenTaylor Test of Hand Function (JTTHF).28 Participants use one hand to perform functional movements, including flipping cards, manipulating/placing small objects, simulated eating, checker stacking, and manipulating cans. The outcome is the time (seconds) to perform movements. To quantify how the hands function together, we employed the Assisting Hand Assessment (AHA).29,30 The AHA quantifies the effectiveness of assisting hand use in performing bimanual activities in children with unilateral upper limb disabilities. The AHA has excellent validity, reliability (0.97-0.99), and responsiveness to change.8,29 The test was videotaped and scored off-site by an experienced blinded evaluator. Scores were computed as transformed logits (AHA units). To measure performance and satisfaction levels in functional goals, we employed the Canadian Occupational Performance Measure (COPM).31 The COPM is a standardized measure that identifies goals and detects changes in self-care, productivity, and leisure performance areas. Through interview, the caregiver identified the child’s functional goals and ranked their importance. They rated satisfaction and performance of each goal (maximum 5). Mean performance and satisfaction scores were analyzed. Both groups of children set goals, but only the structured group practiced goals during the intervention.
(FCR) muscles bilaterally. TMS details are presented in Supplementary Materials. Each child’s TMS map was colocalized to their structural magnetic resonance imaging (MRI), to allow motor mapping that was consistent between each time point. Details are presented in Supplementary Materials. TMS-evoked motor responses were recorded with surface EMG electrodes. Electrodes were connected to a Brainvision ExG amplifier (NeuroConn, Ilmenau, Germany). TMS pulses were first delivered to the affected hemisphere to search for an EMG response (motor evoked potential [MEP]) of the affected FDI. If an MEP of the affected FDI could not be elicited in the affected hemisphere, the uninjured hemisphere was probed for MEPs of the affected FDI. In all cases, if an MEP of the affected FDI or FCR was not found in the injured hemisphere, it was found in the uninjured hemisphere. We determined the threshold for provoking an MEP. The TMS coil was held at the location that provoked the largest FDI response (“hotspot”). MEPs were evoked beginning at a suprathreshold stimulus intensity. Stimulator output was lowered at 2% increments. The lowest stimulator output at which MEP responses of the affected FDI could be elicited from 5 of 10 pulses was defined as the motor threshold (MT). An MEP was categorized as a response if the latency between the TMS pulse and MEP onset was less than 40 ms, and if the amplitude of the MEP was at least 50 µV. After the MT was determined, a circular grid was superimposed onto the child’s MRI using Brainsight. The grid was centered at the affected FDI hotspot. Grid spacing was 1 cm. The grid consisted of 5 concentric rings, resulting in a grid with a 5 cm radius (81 grid points). Single TMS pulses (3-6 per site when an MEP was found, 1-2 per site when no MEP was found) were delivered to each grid point, starting at the hotspot and moving concentrically along the grid, ending at the outermost ring. Stimuli were delivered at an intensity of 110% affected FDI MT, frequency .3). Six children (5 structured, 1 unstructured) had motor maps of the affected hand in both hemispheres—that is, bilateral motor maps. There was a strong asymmetry in map size of the 2 sides. In 5 of the 6 cases (4 structured, 1 unstructured), the map in the injured hemisphere was approximately double the size of the map in the other hemisphere (ratio, injured–uninjured hemispheres = 1.95, SD = 0.11). For these cases, we used the map in the injured hemisphere for analysis. In the remaining child with bilateral maps (structured group), the map of the affected FDI and FCR was 4.75× larger in the uninjured hemisphere than the injured hemisphere, and the map in the uninjured hemisphere was used for analyses.
Changes in Motor Maps After Bimanual Training
Figure 2. Coronal MRI slices showing a cross-section of each child’s lesion.
The color of the frame surrounding the MRI indicates the CST laterality of the child (black = contralateral, white = bilateral, gray = ipsilateral). The yellow asterisk indicates the side of injury.
hand. There was also an overall improvement in COPMSatisfaction (Figure 1D; F[2, 17] = 15.77, P < .001) but no interaction between COPM-Satisfaction and training type (F[2, 17] = 1.76, P = .20). Both groups improved a clinically meaningful amount in COPM-Performance and Satisfaction. Improvements in all measures were maintained 6 months after therapy, as there were no statistically significant changes between the immediate posttraining and 6 months posttraining measures for either group.
Laterality of Motor Map Controlling the Impaired Hand We determined the location of the motor map of the affected hand (Table 1, Figure 2). Children were categorized as contralateral if 100% of TMS responses in the affected hand resided in the same hemisphere as the lesion. Children were categorized as ipsilateral if 100% of TMS responses in the affected hand resided in the opposite hemisphere as the
We examined changes in motor maps after structured skill training or unstructured practice. Figure 3 shows representative motor maps from one child per group. Map size increased in the structured (1A-1C), but not the unstructured group (2A-C). After training, there was a significant interaction between map size (FDI + FCR) of the affected hand and training type (F[2, 17] = 4.7, P = .036). There was a significant increase in map size of the affected hand in the structured skill group (pre-post training P = .009, 23.3% increase; pretraining to 6 months posttraining P = .047, 34.9% increase) but not in the unstructured practice group (P > .3; .2). The map size for the affected FCR did not change significantly in the structured skill group immediately after training (P = .85, 6.1% increase) but was significantly greater than baseline 6 months after training (P = .049, 42.2% increase). In the unstructured group, FCR map size did not change after training (P > .3). Amplitude of motor responses to TMS increased significantly (Figure 4) after structured skill training but not unstructured practice (Figure 4D-E). There was a significant interaction between average MEP of the affected FDI and treatment group (F[2, 17] = 4.21, P = .033). The structured skill group showed a significant increase in FDI MEP size from pretraining to 6 months posttraining (P < .0001, 19% increase), though not from pretraining to immediately following or immediately following to 6 months later. There was no significant change in FDI MEP size in the unstructured practice group (P > .8). There was a significant
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Figure 3. Changes in motor maps after training.
Colored dots represent movement evoked by TMS at that site. (A1-C1) Structured skill training, representative maps of the affected hand from one child. (A2-C2) Unstructured practice, representative maps of the affected hand from one child. (D) Quantification of map changes. The size of the motor map of the affected hand increased significantly only in the structured training group (*P < .05).
interaction between average MEP of the affected FCR and group (F[2, 17] = 4.96, P = .019). The structured skill group showed a significant increase in FCR MEP size from pretraining to 6 months posttraining (P < .0001, 78.1% increase) but not pretraining to immediate posttraining. There was no significant change in FCR MEP size in the unstructured practice group (P > .9).
Plasticity of Ipsilateral Versus Contralateral Maps We determined the location of the motor map of the affected hand (Table 1). There was no difference in the distribution of hand map laterality (contralateral or ipsilateral to affected hand) between groups (Fisher’s, P = .85). Representative maps are shown in Figure 2 (contralateral) and Figure 3 (ipsilateral). Both ipsilateral and contralateral maps expanded after structured skill HABIT (F[2, 8] = 4.6, P = .048). The magnitude of map changes were not different in children with an ipsilateral versus contralateral CST (F[2, 7] = 0.32, P = .74).
Associations Between Map Changes and Hand Function Changes Children in the structured skill group who showed the most improvement in COPM-Performance also had the largest changes in hand map size (Supplemental Figure 1, F[1, 8] = 7.5,
P = .013, r = .54, r2 = .30). Children with larger improvements in JTTHF showed larger expansions of the hand motor map (F[1, 8] = 5.6, P = .045, r = .64, r2 = .41). There was not a significant association between hand map change and improvement in the AHA (P = .95, r = .02). In the unstructured group, there were no significant associations between map changes and JTTHF, AHA, or COPM changes (P > .3, r < .35). Importantly, baseline hand function and amount of recovery was not related to whether the child’s map of the impaired hand was located in the injured or uninjured hemisphere (JTTHF F[1, 18] = 4.82, P = .10; AHA, F[1, 18] = 1.4, P = .24; COPM Performance, F[1, 18] = 0.42, P = .48, no interactions).
Stability of Motor Maps in the Absence of Intervention We show the stability of motor maps in the absence of intervention (Supplementary Materials).
TMS Safety Outcomes Of the 70 TMS sessions conducted in this study, 2 participants reported mild headache after 4 (5.7%) of the sessions, 3 participants reported discomfort in the headband used for neuronavigation after 5 (7.1%) of the sessions, and 2 participants reported discomfort with sitting for an extended
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Figure 4. Changes in magnitude of motor evoked potentials in TMS maps after structured skill training.
(A1-C1) Maps of the affected hand located contralateral to the affected hemisphere in a representative case. Red color indicates stronger MEP response. (A2-C2) Representative maps of the affected hand in a representative case from the unstructured practice group. (D-E) MEP amplitude of the representation of the affected FDI increased significantly after structured but not unstructured training (*P < .05).
period of time after 3 (4.3%) sessions. All side effects resolved without treatment within 1 hour after TMS. No serious adverse events occurred.
Discussion This is the first study, to our knowledge, to examine the critical ingredients of bimanual training that drive changes in motor cortex physiology in children with USCP. We compared bimanual structured skill training and unstructured practice. The study uncovered 3 main findings: (a) skill training increased the size and strength of the motor map of the affected hand, (b) unimanual skill of the affected hand and performance of functional goals were correlated with increased map size, and (c) Motor maps were plastic whether they resided in the hemisphere contralateral or ipsilateral to the affected hand. Our findings are consistent with studies showing that repetitive practice of a specific motor skill drives map plasticity.2,11,12,33-35 In animal models of stroke and USCP, and in human stroke patients, constraint of the unaffected forelimb, plus skill training of the affected forelimb, can improve motor skill and expand the motor map of the affected limb.21,22,36-40 In human stroke patients, the magnitude of map expansion was correlated with improvements in skill.41 Training has also been shown to increase fMRI activations in secondary motor and cerebellar regions.42
Importantly, constraint alone, without skill training, does not change motor maps.2,11 Though further work is needed to uncover the mechanisms of cortical plasticity associated with skill-based neurorehabilitation, work in animal models has determined that skill training, but not unskilled motor activity, increases densities of synapses, dendritic arbors, and spines in the motor networks.43 These changes are associated with increases in neurotrophin expression44 and increased density of spinal interneurons.2 We found that structured and unstructured therapy both resulted in equal improvements in unimanual movement speed and bimanual use. It is possible that the 2 groups had differences in movement kinematics or other more detailed measures of movement quality, since the clinical outcome measures we used do not quantify the quality of movements. Further studies should examine kinematics of motor recovery in children with USCP. We found that functional gains and changes in cortical plasticity were independent of hemisphere of control, that is, ipsilateral or contralateral to the affected hand. Constraint-induced movement therapy studies in children with USCP suggested that in children with ipsilateral control of the affected hand, improvements in movement speed45 and changes in M1 excitability17 were less robust than for children with a contralateral CST. However, we found that ipsilateral control of the affected limb showed
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Friel et al similar amounts of plasticity as contralateral control. Ipsilateral pathways have the capacity to be adaptive, functional, and plastic,46-48 though a larger study is needed to better understand differences in plasticity of different hemispheres of control. This study uncovers a dichotomy of neuroplasticity. The unstructured practice group, which improved hand function, did not show motor cortex plasticity in TMS maps. The high dose (90 hours) may have washed out group differences. Lower dosages could result in differences between groups. While we did find a positive association between functional gains and cortical plasticity, it is possible that with lower doses, associations between motor outcomes and plasticity would be more apparent in the structured skill group than the unstructured group. Changes in motor function can occur without causing changes in motor maps.2,9 Some improvements in motor skill can be driven by existing motor networks, while more robust changes in motor skill are associated with rewiring of motor pathways.49 It is also likely that plasticity occurred in brain regions other than M1, such as secondary motor areas, sensory networks,50-52 subcortical brain structures,53 and spinal interneuronal systems.2,35,54 It is likely that plasticity in these systems underlies the motor improvements seen in the unstructured practice group. Further studies, specifically those that can measure plasticity in different brain regions, are needed to examine plasticity in other systems during rehabilitation. The relative timing of motor map changes and improvements in motor skill has been studied in animal models of stroke and USCP. Behavioral improvements after infarct plateaued before changes in motor maps could be detected.55,56 In contrast, in USCP, map changes were found after pharmacotherapy57 or constraint-induced movement therapy2 that preceded motor recovery. It is possible that intensity of the structured skill group was sufficient to drive motor map plasticity, but that a longer duration of unstructured practice may have been needed to change motor maps. The current findings show that skill training is a critical ingredient for driving motor cortical plasticity in children with USCP. While both groups improved in clinical outcomes, the structured skill training group showed the most improvement in functional gains. This work and other evidence58 indicate that skill training is an important ingredient in neurorehabilitation strategies.
Methods that examine cortical plasticity throughout the brain, such as functional MRI and electroencephalography, can determine other locations of plasticity associated with hand rehabilitation. We discuss challenges of applying our methods to children with USCP in Supplemental Materials. Finally, clinical outcomes reported here measure indirect aspect of movement quality. Further study of movement quality is needed to explore the relationship between cortical plasticity and rehabilitation outcomes.
Conclusions Structured and unstructured bimanual training improved hand function in children with USCP. Skill training produced stronger improvements in functional goals. There was a dichotomy between these improvements and cortical plasticity. Only skilled training induced motor map plasticity. Further work is needed to examine the interplay between cortical physiology and motor skill improvements. Acknowledgments We thank Ya-Ching Hng, Electra Petra, Ashley Chinnan, and the volunteer interventionists. We thank Stephen Dashnaw and Glenn Castillo for MRI acquisition. We thank Drs Peter Bulow and Joshua Berman for performing screening exams. We thank the participants and their families.
Authors’ Note None of the sponsors were involved in the preparation of the manuscript or decision to submit for publication.
Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Funded by NS062116 (KMF), Columbia Professional Schools Diversity Award (KMF), and NIH CTSA Award (KMF) (KL2 RR024157, UL1 RR024156, TL1 RR024158). Each of these sponsors provided funding based on the design of the study. Funds were used to pay for equipment and personnel needed for data collection, management, analysis, and interpretation.
References
Limitations This study has several limitations. The relatively low number of participants limits generalizability. While we did match groups on baseline JTTHF and age, there were differences between groups in the distribution of CST projection patterns. Second, this study only measured M1 plasticity.
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